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OnPay søger en AI Enabler til at lede adoptionen af agentic AI-værktøjer og Udvikleroplevelsen i Payments-teamet. Rollen kræver hands-on teknologisk formåen og vil sætte standarder for, hvordan AI-støttet udvikling flyder gennem planlægning, kodegennemgang og produktion.
Du vil eje værktøjskæden, evaluere og konfigurere stacken (Claude Code, Devin, Copilot, Replit mv.), og sikre overholdelse af PCI DSS i en regulatorisk kontekst. Hybrid arbejde og mulighed for ledelsesopgaver er en del af pakken.
You will be joining the payment solution OnPay as part of a team dedicated to growing our presence across Europe. Online payments are becoming more prevalent every day and our mission is to support our growing merchants by remaining at the forefront of product offerings and reliability. This is where you come in.
As a team, we collaborate on the entire software development lifecycle where security and compliance are fundamental to OnPay's success and require high attention to detail to ensure that the millions of transactions we process monthly remain secure and seamless.
We are seeking an AI Enabler to lead the adoption, evolution, and day-to-day enablement of agentic AI tooling and developer experience (DevX) across the Payments team.
The ideal candidate is a hands-on technologist with a strong appetite for staying at the absolute forefront of AI-assisted development – testing emerging tools, integrating them into real workflows, and turning the team into a proof-point for what an AI-native engineering organisation can deliver.
Reporting to the Software Director, the AI Enabler works day-to-day as part of the team's enabling functions, taking direction from the Architect, Tech Lead, and Frontend Lead on priorities and integration points, while owning the toolchain and enablement approach independently. The role is explicitly enabling – success is measured by the team's velocity and quality, not the AI Enabler's individual ticket throughput.
While the core of this role is enablement, the right candidate can pick up line management of the Payments team (around four people) from day one – 1:1s, performance and development conversations, hiring decisions, and owning team priorities, direction, and overall health. This is for someone ready to step into a traditional people management role on top of a strong technical foundation – not a purely technical leadership track.
Enable the team – Embed agentic workflows across planning, development, code review, QA, and production monitoring. Pair with engineers, run hands-on sessions, and remove friction so the team can fully leverage AI tooling in their daily work.
Own the agentic toolchain – Evaluate, select, configure, and maintain the team's AI development stack (Devin, Claude Code, Replit, Copilot, MCP servers, agent frameworks, etc.). Define standards, guardrails, and best practices so adoption is consistent and safe.
Stay on the forefront – Continuously test, benchmark, and adopt new agentic tools and techniques as the field evolves. Track upstream developments (model providers, agent frameworks, IDE integrations) and downstream impact (delivery velocity, code quality, incident rates) – and translate both into concrete actions for the team.
Redesign the workflow – Work with the Architect, Tech Lead, and Product Manager to redesign delivery around agent-assisted sprints – prototyping, architecture documentation, AI-assisted MR review, AI-assisted test generation, and autonomous production issue triage.
Compliance and governance – Ensure agent-generated code in a PCI DSS Level 1 environment meets regulatory and security expectations. Define review gates, audit trails, and guardrails that make agentic development safe by default.
Spread the practice – Document what works, share learnings, and act as a proof point and reference for other team.blue teams adopting AI-native ways of working. Help shape the broader organisation's playbook.
Documentation and knowledge capture – Own the documentation of the team's AI tooling, agentic workflows, prompts, guardrails, and operating practices – both structuring how it lives and actively maintaining it. Essential for PCI auditability and for ensuring the knowledge compounds and can be re-used as the team and organisation grow.
Hands-on contribution – When it accelerates the team, contribute directly by building internal tooling, automations, prompts, agent configurations, MCP integrations, or developer experience improvements that create value across the entire engineering organisation.
Measure and iterate – Define and track meaningful metrics for AI-assisted delivery (velocity, quality, review time, incident rate). Run experiments, learn fast, and continuously optimise the toolchain and development process.
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